Data-Driven Smart Eco-Cities of the Future: An Empirically Informed Integrated Model for Strategic Sustainable Urban Development

Abstract

The eco-city is seenas a major force in the overall transition toward a more sustainable urban development paradigm, acting as a set of exemplary techno-environmental solutions for social transformation. However, the scale and rate of urbanization fundamentally disrupt the challenges that eco-cities must contend with. This is coupled with the increased need to understand, plan, and manage eco-cities in new and innovative ways. On this account, transformative processes and practices within eco-cities are being highly responsive to a form of data-driven urbanism as a more effective way to address and overcome the kinds of challenges that eco-cities are designed to solve. That is, eco-cities are increasingly embracing and leveraging what smart cities have to offer in terms of data-driven technologies and applied solutions in an effort to monitor, evaluate, and improve their performance with respect to sustainability—under what has been termed “data-driven smart eco-cities.” The aim of this paper is to develop an integrated model for strategic sustainable urban development based on empirical research in the form of case studies. This model combines and integrates the leading global paradigms of urbanism—namely eco-cities, data–driven smart cities, and environmentally data-driven smart sustainable cities—in terms of their strategies and solutions. The main contribution of this study lies in providing an innovative way of building future models for sustainable urban development, as well as practical insights into developing strategic planning processes of transformative change toward sustainability based on integrated approaches. The proposed model serves to facilitate progress toward achieving the long-term goals of sustainability for those cities that are badging or regenerating themselves as eco-cities, or manifestly planning to be or become smart eco-cities in the era of big data.

Keywords:

• Data-driven smart cities
• data-driven smart eco-cities
• data-driven technologies
• eco-cities
• strategies
• strategic planning
• pathways

Introduction

The increased pressure on cities has led to a stronger need to build sustainable cities that last. Designing sustainable cities of the future, educated by the lessons of the past and anticipating the challenges of the future, entails articulating a multi-scalar vision and these key principles—energy, ecology, infrastructure, waste, livability, mobility, accessibility, economy, and culture—while concurrently responding to major societal and intellectual trends and paradigm shifts in science and technology. Sustainable cities have been the leading global paradigm of urbanism, and eco-cities are one of the most advocated models for sustainable urban development (Bibri & Krogstie, 2021). It is argued that the eco–city model is able to achieve the key objectives of environmental sustainability and to produce some economic and social benefits of sustainability (e.g. Bibri & Krogstie, 2020a; Joss et al., 2013; Kenworthy, 2006; Rapoport & Vernay, 2011; Suzuki et al., 2010). The environmental goals of sustainability dominate in the discourse of the eco-city (e.g. Mostafavi & Doherty, 2010; Holmstedt et al., 2017; Pandis Iverot & Brandt, 2011; Yigitcanlar & Dizdaroglu, 2014) compared to the economic and social goals of sustainability (Bibri, 2021a, 2021b). Still, the mission of Urban Ecology seeks to create eco-cities based on a number of principles that are intended to achieve the goals of sustainability (Roseland, 1997). To totally change the pattern of urban development, and to implement the development strategy of the eco-city, is the most effective way to create sustainable development (Platt, 2004). Therefore, eco-city projects are becoming increasingly prevalent in strategic policy, enviro-economic, and politico-economic discourses worldwide and on this account gaining strong momentum in research agendas in various disciplines (e.g. Bibri, 2021a, 2021b; Bulkeley & Castán Broto, 2013; Caprotti, 2014; Cugurullo, 2016; Joss & Molella, 2013; Joss et al., 2013; Rapport, 2014 ). It is important to take modern ecological civilization and ecological restoration to guide and manage all economic and social activities of the city. Especially, cities have become a focal point for efforts to transition toward a more sustainable, low-carbon society, with many city government or municipal agencies championing eco-city or eco-district initiatives of one kind or another.

In recent years, the development of sustainable urban districts, especially eco-city districts, has attracted increased interest and become an expansion route for many growing cities (e.g. Joss, 2015; Medearis & Daseking, 2012; Pandis Iverot & Brandt, 2011), as well as a common way to address and implement sustainability in the built environment (Joss, 2015; Sharifi, 2013). However, the development of new sustainable urban districts is often subject to more rigorous sustainability objectives with respect to their evaluation in order to meet future challenges (Pandis Iverot & Brandt, 2011). Consequently, recent research within eco-urbanism has started to focus on the three dimensions of sustainability in terms of benefits and shortcomings (e.g. Bibri, 2020a; Bibri & Krogstie, 2020a; Khan et al., 2020; Randeree & Ahmed, 2019). This implies that the eco-city continues to strive toward reaching the status of urban sustainability by reducing material use, lowering energy consumption, mitigating pollution, and minimizing waste, as well as improving social equity, well–being, and the quality of life. Eco-urbanism has taken on a salient position in policy and political discourses focused not only on the environment, but also on economic, social, and technological transitions (e.g. Bibri, 2021b; Caprotti, 2014, 2020; Cugurullo, 2016; Khan et al., 2020; Rapoport & Vernay, 2011). Eco-cities have been conceptualized as materializations of trends toward developing and implementing urban socio-technical and enviro-economic experiments (Bulkeley & Castán Broto, 2012; Castán Castán Broto & Bulkeley, 2013).

T he motivation for achieving the Sustainable Development Goal (SGD) 11 of the United Nations’ 2030 Agenda—Sustainable Cities and Communities in terms of making cities sustainable, resilient, inclusive, and safe (United Nations, 2015a) has increased the need to understand, plan, and manage eco-cities in new and innovative ways. These are increasingly based on more advanced forms of ICT, especially the Internet of Things (IoT) and big data technologies. The United Nations’s 2030 Agenda regards advanced ICT as a means to promote socio–economic development, restore and protect the environment, increase resource efficiency, upgrade legacy infrastructure, and retrofit industries based on sustainable design principles (United Nations, 2015b). This relates to the multifaceted potential of smart cities with respect to the growing role of big data technologies and their novel applications in strategic sustainable development. The main objective of the smart city is achieving heightened economic development, the quality of life, and different sustainability targets through the use of data and technology (e.g. Ahvenniemi et al., 2017; Batty et al., 2012; Bibri, 2019a, 2019b; Bibri & Krogstie, 2020b; Mundada & Mukkamala, 2020). The explosive growth of urban data, coupled with their analytical power, opens up new windows of opportunity for innovation in eco-cities. This means finding more effective ways of incorporating sustainability into the environmental, economic, and social forms of eco-cities.

However, the conscious push for eco-cities to become smarter and thus more sustainable in response to the recent paradigm shift in science and technology brought on by big data science and analytics is motivated by the increased need to tackle the problematicity surrounding their operational management mechanisms, development planning approaches, as well as fragmentary design and technology solutions. This problematicity, which is in both discourse and practice, is manifested in the kind of contradictory, uncertain, weak, non-conclusive, and questionable results produced by research on eco-cities (e.g. Bibri & Krogstie, 2017, 2019; Caprotti, 2014; Cugurullo, 2018; Farreny et al., 2011; Hodson & Marvin, 2010; Kärrholm, 2011; Pinder, 2005). Hence, it is argued that more innovative solutions and integrated strategies are needed in order for eco-cities to address and overcome the kinds of problems, issues, and challenges they are dealing with and thus make actual progress toward achieving sustainability. Smart technologies are socially constructed as the response to almost every facet of the contemporary urban questions (Bibri and Krogstie, 2016), and smart urbanism is being represented as a panacea to the majority of problems facing contemporary cities. As enacted by national governments, supranational agencies, and technology companies, the discourse of smart urbanism claims a supremacy of urban digital technologies for managing and controlling infrastructures, achieving greater effectiveness in managing service demand and reducing carbon emissions, developing greater social interaction and community networks, providing new services around health and social care, and so on (Marvin et al., 2015).

Therefore, eco-cities are increasingly embracing and leveraging what smart cities have to offer in terms of big data technologies and their novel applications in an effort to monitor, evaluate, and improve their performance with respect to sustainability, especially its environmental and economic dimensions (e.g. Bibri, 2020b, 2021b; Bibri & Krogstie, 2020c; Caprotti, 2020; Caprotti et al., 2017; Jolivet & Cowley, 2018; Shahrokni et al., 2014; Shahrokni et al., 2014; Shahrokni et al., 2015; Späth, 2017; Tan et al., 2017)—under what has been termed “smart eco-cities” or “data-driven smart eco-cities.”

This paper aims to develop an integrated model for strategic sustainable urban development based on empirical research in the form of three case studies: (1) eco-cities (Bibri & Krogstie, 2020a); (2) data–driven smart cities (Bibri & Krogstie, 2020b); and (3) environmentally data-driven smart sustainable cities (Bibri & Krogstie, 2020c). This model combines and integrates these leading global paradigms of urbanism in terms of their strategies and solutions. It serves to facilitate progress toward achieving the long-term goals of sustainability for those cities that are badging or regenerating themselves as ecological, or manifestly planning to be or become smart ecological in the era of big data.

This paper is organized into five sections. Section “Research Methodology” briefly describes and outlines the research methodology adopted in this study. Section “Results: An Integrated Model for Strategic Sustainable Urban Development” presents the results. Section “Discussion” discusses the results. This paper ends, in Section “Conclusion,” with concluding remarks together with a conceptual structure of the integrated model for strategic sustainable urban development.

Research Methodology

This study employs case study approach to develop an integrated model for strategic sustainable urban development. The case study approach, which is described in more detail by Bibri (2020c), was used to illuminate the urban phenomena of eco-cities, data–driven smart cities, and environmentally data-driven smart sustainable cities by examining and comparing two cases within each of these analytical frameworks from a total of four of the ecologically and technologically leading cities in Europe. Generally, case study is a descriptive qualitative approach that is used as a tool to study specific characteristics of a complex phenomenon. This approach involves describing, analyzing, and interpreting that phenomena. This pertains, in this context, to the prevailing conditions related to plans, projects, and achievements. Specifically, how the four selected cities behave as to what has been realized, the ongoing implementation of plans, and the execution of urban projects. This is based on the corresponding practices and strategies for sustainable development and technological development. To obtain a detailed form of knowledge in this regard, a five-step process tailored to each of the three case studies was adopted (Table 1).

Table 1. A five-step process tailored to each of the three conducted case studies.

Eco-cities

Using a narrative framework that focuses on the eco-city as a real-world problem and provides essential facts about it, including relevant background information. Introducing the reader to key concepts, models, and design strategies relevant to the problem under investigation. Discussing benefits and research gaps and issues relevant to the problem under investigation. Explaining the actual solutions in terms of plans, the processes of implementing them, and the expected outcomes. Offering an analysis and evaluation of the chosen solutions and related issues, including strengths, weaknesses, tradeoffs, and lessons learned.

Data-driven smart cities

Using a narrative framework that focuses on the data-driven smart city as a real–world problem and provides essential facts about it, including relevant background information. Introducing the reader to key concepts, technologies, and data-driven smart sustainable urbanism processes and practices relevant to the problem under investigation. Providing an overview of the literature review previously conducted in relation to the study, which delivers a comprehensive, state–of–the–art review on the sustainability and unsustainability of smart cities in relation to big data technologies, analytics, and application in terms of the underlying foundations and assumptions, research problems and debates, opportunities and benefits, technological developments, emerging trends, future practices, and challenges and open issues. Explaining the actual solutions in terms of plans, the processes of implementing them, and the expected outcomes. Offering an analysis and evaluation of the chosen solutions and related issues, including strengths, weaknesses, tradeoffs, and lessons learned.

Environmentally data-driven smart sustainable cities

Using a narrative framework that focuses on data-driven smart solutions and their role and potential in improving and advancing environmental sustainability in the framework of the smart sustainable city as a real–world problem, and provides essential facts about it, including relevant background information. Introducing the reader to key concepts, core enabling technologies, infrastructures, landscapes, frameworks, as well as urban operating systems and urban operations centers, all with relevance to the problem under study. Identifying the commonalities and differences between the two cities with respect to the emerging technologies. Explaining the actual solutions in terms of plans and visions, the processes of implementing them, and the realized and expected outcomes. Offering an analysis and evaluation of the relevant solutions and related issues, including strengths, weaknesses, and lessons learned.

The objective of the three case studies carried out on contemporary real-world phenomena is to inform the theory and practice of data-driven smart eco-cities of the future as an integrated and holistic paradigm of urbanism by illustrating what has worked well, what needs to be improved, and how this can be done in the era of big data. These case studies are particularly useful for illustrating the general principles underlying these phenomena, for understanding how different elements fit together and (co-)produce the observed impacts in a particular urban context based on a set of intertwined factors in the context of these phenomena, as well as for generating new ideas about and research questions regarding the relationships between these phenomena.

Results: An Integrated Model for Strategic Sustainable Urban Development

This model should look at the wider picture and be flexible in the choice of its means with respect to the integration of the relevant infrastructures of data-driven smart eco-cities of the future. Different, yet related, strategies as a set of plan or goals are needed in order to bring about the needed transformations associated with these infrastructures. To employ or execute each of these strategies in turn requires a set of clear pathways as ways of achieving specified results. These pathways are the specific actions, sequences of actions, and agendas that need to be taken within each strategy. However, as data-driven smart eco-cities generally need to be able to respond to new global shifts or technological changes, it is important to keep in mind that both strategies and pathways need to have some degree of flexibility. The strategies as a form of long-term plan may need to pivot in response to different shifts or changes. The pathways remain flexible in regard to any potential adjustment and modification. However, determining the strategies and the pathways to execute these strategies is the main part of the effort to be made to achieve the status of data-driven smart eco-cities of the future. The key strategies and pathways are presented next in accordance with the following four infrastructures of data-driven smart eco-cities of the future:

1. Green infrastructure

2. Smart sustainable urban infrastructure

3. Economic infrastructure

4. Social infrastructure

Green Infrastructure

Ecological design is a form of design that integrates itself with living processes to minimize environmentally negative or destructive impacts. As an integrative, ecologically responsible approach, ecological design involves greening as an important design concept for sustainable urban forms. Green space has the ability to contribute positively to the key agendas of sustainability in urban areas (Swanwick et al., 2003). It refers to the areas of nature found in the urban landscape, including trees, grassy patches, flowerbeds, rock gardens, sports fields, woods, lakesides, and water features. Green space has numerous benefits, including improving health and wellbeing, ameliorating the physical urban environment by removing CO2 emissions and other toxins from the air, enhancing the esthetics of urban areas and thus making them more pleasant, increasing the urban image and economic attractiveness, as well as controlling storm runoff (Bibri, 2021b). In particular, the research in this area tends to focus on the health advantages of urban green space (e.g. De Vries et al., 2002; Maas et al., 2006).

At the core of ecological design is green infrastructure, a strategically planned network of natural and semi-natural areas with other environmental features that are designed and managed to deliver a wide range of ecosystem services, including water purification, air quality, space for recreation, climate mitigation and adaptation, flood protection, temperature regulation, biodiversity, and local stormwater management. Green structure encompasses large green spaces, waterways and streams, shorelines, parks, natural land, and forests as one common structure. As an ecological strategy, green infrastructure emphasizes the benefits and losses of natural environmental and map green resources by assessing the associated natural and recreational qualities. This strategy can be broken into the following eleven substrategies:

1. Greening

2. Rainwater harvesting

3. Ecological diversity

4. Biodiversity

5. Green parks

6. Green streets and alleys

7. Green factor and green points

8. Green roofs

9. Rain gardens

10. Bioswales

11. Permeable pavements

The green infrastructure strategy relates to the idea of letting nature do the work by designing multifunctional green infrastructure to provide important ecosystem services of various categories, including provisioning, regulating, cultural, and supporting services. To let nature do the work entails ensuring that greenery and water are used as active components in the design and operation of the city. The green structure replaces and complements technical systems, creates a richer plant and animal life, and contribute to human health and well-being. Important to note is that the green infrastructure strategy as an integrated approach is best to be implemented in new urban areas or outer areas with development potential. Below are the key pathways for executing the green infrastructure strategy:

• Ensure the use of greenery and water as active components in the design and operation of the city.

• Provide incentives to residents to install their own rainwater harvesting systems that connect to a gutter system or other rooftop water collection network and store the rainwater in a barrel for later non-potable use (e.g. watering plants, flushing toilets, and irrigation).

• Design the drainage system in such a way to be esthetically pleasant, with waterfalls, canals, ponds, and various elements for purifying and buffering the water.

• Divert the rainwater through aboveground gutters surrounding the buildings of the new city districts as part of public space design.

• Build green roofs to reduce the amount of rainwater to be drained. The rainwater is slowed down by green roofs and travels through them, into ponds in the courtyards where it is partially cleaned by the ora, as well as public spaces before it is transported into open canals along the streets to run out into the sea.

• Build permeable pavements to reestablish a more natural hydrologic balance and to reduce runoff volume by trapping and slowly releasing precipitation into the ground instead of allowing it to flow into storm drains and out to receiving waters as effluent.

• Build bioswales to slow and reduce stormwater runoff while removing debris and filtering out pollutants.

• Build rain gardens to collect and hold rainwater from downspouts, driveways, and sidewalks for a short time, allowing the water to slowly seep back into the ground. When planted with the right types of plants, rain gardens also attract birds, butterflies, and other wildlife.

• Implement green space factor as an instrument to guarantee a certain volume of greenery in residential courtyard and to ensure that green qualities are achieved in connection with the city’s new construction projects.

• Use green space factor where appropriate and develop it to be more applicable in different contexts to contribute to good living conditions for humans, animals, and plants.

• Ensure that the green space factor system involves not only the greening of the inner courtyards with plenty of vegetation and ponds, but also green roofs and climbing plants on the walls.

• Monitor and improve the effects of green space factor pertaining to such ecosystem services as recreation, reduced risks of flooding, improved local climate, and noise reduction.

• Reinforce ecosystem services in urban planning, maintenance, and management so that their benefits and functions do not deteriorate.

• Supplement the green factor system with green points, a list of a number of wide–ranging environmental measures, that can be implemented to promote biodiversity in the city. A particular set of green points can be determined to be implemented in every residential courtyard, such as bat nesting boxes, butterfly flower beds, country gardens, and soil depth to grow vegetables.

• Transform the existing green and water views across the city into livable waterfront areas offering plaza, green space, and promenade, allowing for a variety of activities to take place, and providing great opportunities for the social mix and interaction of residents.

• Use the waterfront footpath as linkages to several landscape nodes.

• Create and distribute parks across the city by ensuring 100% of the existing apartments have access to a park and natural environment within 200 meters, as well as by reserving a sufficient number of hectare for parks and dividing them between these apartments.

• Develop and implement advanced technologies for monitoring the condition and composition of green space across the city.

• Develop and implement new technologies to stimulate biological and ecological diversity and conservation.

Smart Sustainable Urban Infrastructure

The rationale for integrating sustainable urban infrastructure and smart urban infrastructure is to highlight the enabling role and innovative potential of advanced ICT in optimizing and enhancing the operational performance of urban systems and domains in the context of sustainability. As a wide-ranging term, infrastructure is the basic structure that supports the operation of a city, which makes economic and social development possible. Here, the focus is on the essential urban infrastructure that makes up the city, including transportation system, communication system, energy system, waste system, lighting system, sewage system, and waste disposal system. These are associated with the basic facilities, services, and installations needed for the functioning of the city in terms of engineered systems. Smart sustainable urban infrastructure encompasses seven strategies, namely:

1. Smart sustainable transportation

2. Smart sustainable energy

3. Smart sustainable waste management

4. Smart urban metabolism

5. Smart environmental monitoring

6. Smart street lighting

7. Smart urban infrastructure

Smart Sustainable Transportation

To be able to effectively improve and strategically advance the contribution of the city to the goals of sustainability, it is necessary to fully integrate sustainable transportation system with smart transportation system. Accordingly, the smart sustainable transportation strategy encompasses seven substrategies, namely:

1. Walking and cycling

2. Public transport

3. Car-pooling (biogas and electric)

4. Electric vehicles

5. Smart transport management

6. Smart traffic management

7. Smart mobility management

Sustainable Transportation

Sustainable transportation is a major strategy for achieving sustainability. It denotes any means of transportation that is green and has low impacts on the environment. Below are the key pathways for executing the sustainable transportation strategy:

• Implement the hierarchy of sustainable transportation, namely walking and cyclin, public transport, car pools, and private cars.

• Set clear targets for reducing car journeys with the long long–term objective of establishing the hierarchy.

• Provide a range of opportunities for walking and cycling through increased densities and short distances, i.e. proximity to workplaces, shops, services, and facilities in densely residential areas.

• Improve the public transport system by creating new connections, enhancing existing networks, and influencing habits and movements through soft measures.

• Improve the capacity, comfort, waiting time, and service quality of the public transport system.

• Build and enhance pedestrian paths/walking tracks and bike paths/cycle lanes linking different areas of the city to local workplaces, shops, businesses, and facilities.

• Build new cycle bridges linking the new city districts to the city center and the inner city.

• Make good availability of bicycle parking throughout the city.

• Provide incentives that give priority to cycling by offering a higher than average number of cycle parking spaces per apartment, house, and building.

• Restrict car parking by limiting parking spaces per apartment, house, and building.

• Close public spaces to cars and provide further opportunities for walking and cycling along pleasant routes.

• Provide incentives for electric and biofuel cars and taxis.

• Develop and implement strategic plans for the transition from private-owned cars to a plug-in hybrid, to mobility as a service with electric taxis, to biofuel diesel, and to public transport:

  • ○Private cars can be changed to a plug-in hybrid and then replaced by mobility as a service with electric taxis, a small alteration of self-driving electric taxis. An important precondition for the expansion of this traveling mode is the charging stations for electric cars that should be in place across the city.

  • ○Private cars can be changed to a biofuel diesel cars and then to public transport for everyday mobility and renting or sharing a biodiesel for longer trips.

  • ○Gradually increase the percentage of the private cars leaving the different districts of the city and allow a fleet of more and more self-driving electric taxis to circulate in these districts.

• Make buss stops within reasonable distance from blocks of building and with shortest possible running time intervals (e.g. operating on a five-minute schedule).

• Provide hassle–free usage of multiple modes of shared and public transport.

• Use biogas-fuel powered and hybrid busses as well as solar-powered screens showing times of arrival at bus stops.

• Combine measures and initiatives for shaping the physical structure of sustainable transportation as well as influencing behavior.

• Implement mobility management as a soft measure to build, develop, and maintain transport infrastructure and to create and keep the dialogue with different stakeholders as to how to make choices for travel modes.

• Introduce economic, social, and environmental policies through the congestion charges and Ultra Low Emission Zone (ULEZ), and allow the residents to tangibly see the impacts of automobile use across all three pillars of sustainability.

Smart Transportation

Smart transportation is one of the main ways modern cities can improve the daily lives of citizens and sustainability. It involves information systems that collect data about traffic, vehicles, and the use of different modes of transport for further processing and analysis in city operations center. Transport and traffic management is one of the most common areas that use data-driven technology solutions. The key pathways for executing the smart transportation strategy are:

• Develop and implement the unified public transport system with ticketing system.

• Develop and implement the bus transit system based on the orthogonal network of bus lines.

• Manage all the transport services of the city in realtime based on the data received from the situational centers.

• Develop and implement the smart traffic light system.

• Develop and implement the smart parking system.

• Encourage businesses and consumers to use vehicles equipped with telematics.

• Raise awareness of the options and benefits of intelligent transport systems.

• Apply disincentives to alter demand for carbon intensive vehicles.

• Equip public transport with advanced sensors to monitor mobility and movement and collect related data (e.g. precise geo-positioning, times, delays, number of passengers, etc.) for mining and visualization

• Use mobility and movement data for planning in terms of determining the need for launching new public transport routes or developing new road infrastructure.

• Implement the smart board for displaying information about the roads conditions in real time.

• Ensure seamless, efficient, and flexible multi–modal transport system.

• Support equity and inclusion using smartphone apps in sustainable urban transport.

• Develop and implement new business models for “Mobility–as–a–Service” for sharing systems.

• Develop and implement the bicycle sharing system for short trips across the city.

• Develop and promote smart apps for other modes of sustainable mobility to keep the citizens up-to-date and connected.

• Use sensed mobility data to understand how mobility behavior and traffic variation from one day to another is linked to the network topology for developing smart apps to influence travel behavior toward sustainable mobility.

• Integrate real–time mobility data and large–scale datasets that simultaneously record and calibrate dynamical traces of individual and collective movements across various spatial scales and over different temporal scales to understand the dynamic interplay between individual and collective mobility and social interactions.

Smart Sustainable Energy

The smart sustainable energy strategy aims to reduce energy consumption, increase renewable energy adoption, and decrease carbon footprint. Here technological innovations can play a prominent role in the light of the high predicted rate of urbanization. Integrating sustainable energy with smart energy will drive data-driven smart eco-cities of the future to become fossil fuel–free and climate positive. Therefore, the energy system should combine green energy technologies and energy efficiency technologies. Accordingly, smart sustainable energy consists of key four strategies, with some overlaps among them, namely:

1. Smart power grid and advanced metering infrastructure technologies

2. Smart building technologies

3. Smart home monitoring technologies

4. Renewable energy sources and technologies

Smart Power Grid and Advanced Metering Infrastructure Technologies

Both eco-cities and smart cities are increasingly investing in and implementing smart meters, sensor networks, automated control systems, and cyber-physical systems within the framework of the IoT. The goal of smart energy is to achieve energy systems that are highly energy-efficient, increasingly powered by renewable and local energy sources enabled by new technologies, and less dependent on fossil fuels. The main players in the area of smart energy are smart power grid and advanced metering infrastructure. Smart power grid deploys smart meters and communication technologies within electricity networks. It denotes a set of hardware, software, and network tools that enable generators to route power more efficiently to consumers, reducing the need for excess capacity and allowing two–way communication for real-time demand side management. It collects the data received from Wi-Fi enabled sensor network on the level of power supply from diverse sources and then processes and analyzes these data in real-time for decision-making and information transmission for process control to improve the performance of the power grid. Advanced metering infrastructure is a composite technology that consists of solid-state meters capable of remotely providing consumers' electricity use detail (i.e. electric energy, voltage levels, current, power factor) to the utility, a two-way communications channel (i.e. to power suppliers for system monitoring and billing and to consumers for greater clarity of consumption behavior), and a meter data repository and management. Thus, it includes sensors placed on consumers access points and on production, transmission, and distribution systems, as well as remote controls and communication technologies within electricity networks. The key pathways for executing the smart grid and advanced metering infrastructure strategy: integrating and coordinating renewable energy production and consumption and power facilities through enabling technologies, energy services, and active users, are:

• Support projects of smart grid technologies.

• Subsidize projects that support energy efficiency technology adoption.

• Allow decentralization of energy production.

• Promote energy production from renewable sources.

• Promote the multiplication of grid distribution networks.

• Subsidize projects that incorporate renewable energy in power distribution networks.

• Develop and implement integrated renewable solutions that involve the use of modeling, simulation, analytical, and management tools to enable a wide deployment of renewable energy.

• Deploy and implement the large-scale smart grid system comprising:

  • ○Consumer application support in terms of in-home display with real-time usage and pricing statistics, usage aware appliances, and home automation.

  • ○Advanced metering infrastructure allowing usage report by time and outages in real-time, load reduction, remote disconnect-reconnect, operational improvement for distribution/retail companies, and interface to water meters.

  • ○Grid applications drive associated with grid automation, reduction in losses, remote monitoring, and accurate balancing.

  • ○Integrated renewables and distributed energy facilitating integration of back-up generators, storage, and distributed solar, as well as disconnection in case of network overload.

  • ○Integration and use of electric vehicles. Grid technologies that go hand-in-hand with renewables are required in response to the energy demand of the massive adoption of electric vehicles. It is important to develop more effective ways to integrate renewable energy with the grid at scale, and therefore, storage solutions and mechanisms for decentralized energy generation, sharing, and sale are necessary.

Smart Building Technologies

Smart buildings use sensors and controls in buildings to improve efficiency. The building management system (BMS), an overarching computer-based control system (an intelligent distributed network of electronic devices and systems), is responsible for the automatic regulation, control, and monitoring of the building's mechanical and electrical subsystems, such as heating, ventilation, air conditioning (HVAC), lighting, power systems, and security systems. These technical processes are primarily intended to maintain predefined parameters (or set points) and the control of their functionality. BMS employs smart metering and advanced visualization tools to provide real-time monitoring and continuously gather the data on what is taking place in a building and how its equipment is operating and feeding them into a control system to improve energy efficiency. So, the collected data can be used to identify additional opportunities for improvements. Below are the key pathways needed for executing the smart building strategy:

• Subsidize design projects that support efficiency technology adoption and expansion among building owners and operators as well as urban developers.

• Reward the best–in–class buildings’ owners and operators as well as urban developers.

• Provide funding schemes that encourage owners to invest in building automation systems.

• Develop and implement assessment tools for energy-efficient building.

• Regulate the use of automation measures in the construction of buildings and new development projects.

• Use decision-support systems that enable large-scale energy efficiency improvements in existing building stock.

• Evaluate the energy efficiency potential of different building vintages in collaboration with utility companies in the different districts of the city to reduce energy use, depending on the market segmentation pertaining to the date of the construction of buildings.

• Use data-driven smart approach to strategic planning of building energy retrofitting, using data about actual building energy consumption, energy performance certificates, reference databases, and so forth. This allows a holistic city-level analysis of retrofitting approaches and strategies thanks to the aggregated projections of the energy performance of each building, such as energy saving, emissions reduction, and required family or social investment.

• Promote and install BMS in new and retrofitted municipal, commercial, and industrial buildings to monitor and optimize the use of the supervised subsystems.

• Initiate and maintain collaboration between the housing cooperatives and other property owners to procure and explore new technologies and solutions that can help attain the environmental targets set by the city.

Smart Home and Energy Monitoring Technologies

Smart homes allow homeowners to control appliances, lights, and other devices remotely using a smartphone through an internet connection. Smart home technology provides homeowners with convenience and cost savings. A smart device or appliance includes the intelligence and communications to enable automatic or remote control based on user preferences or external signals. Energy monitoring software aims to provide users with information about their consumption patterns by gathering and analyzing relevant data (electricity, heat, gas, water, etc.) using counters or sub-counters present on-site or in the building and then providing useful information directly to the consumer’s device. This shows users how much energy they are using and how it is used at any time of the day. The key pathways needed for executing the smart home and energy monitoring strategy are:

• Promote and install energy star HVAC systems within municipal, commercial, industrial, and residential buildings.

• Promote and install energy star appliances that use a great deal less power than their predecessors.

• Promote and install smart power strips that sense energy demand and cut off power supply to fully charged or not in use devices.

• Promote and install smart meters.

• Promote and install easy-to-use home energy monitoring systems (HEMS).

• Promote and install energy monitoring software on smartphones in case the smart meter is already installed in the house so as to allow to read the information collected by the smart meter.

• Install energy monitoring systems in municipal buildings for obtaining information about energy consumption, such as electricity meter, electricity ambient conditions, internal ambient conditions, and temperature. Workers can be reminded instantly based the smart monitoring results for taking simple and quick actions to help reduce GHG, especially with the help of fog devices in the fog smart computing paradigm.

• Promote intelligent monitoring systems that flag potential faults in real time and indicate what energy-saving measures can solve the problem by relying on such KPIs as the patterns relating to specific areas of energy consumption, intensity of energy usage, and other indicators that can be of use in establishing energy targets.

• Make timely decisions and policies on top of the smart monitoring results of GHG in city-wide environments and infrastructure.

Renewable Energy Sources and Technologies

It is important to strongly advocate renewable energy generation and usage in order to enable the city to become fossil fuel–free by 2050. Renewable energy is derived from naturally replenished and zero-emission sources such as solar, wind. biomass, hydropower, and geothermal), using a number of industrial and technological systems. Below are the key pathways needed for implementing the substrategy of renewable energy sources and technologies:

• Install solar collectors on the top of new and retrofitted buildings throughout the city to produce heat.

• Install pumps (aquifer and sea water) to produce heat.

• Use aquifer and heat pumps for cooling.

• Combine solar collectors and pumps to aggregate heat production.

• Promote and install solar panels/photovoltaic cells throughout the city to produce electricity.

• Install stations of wind turbines to produce electricity for heat pumps as well as dwellings.

• Complement windmill farms by installing wind generators, smaller versions of massive power generators, in the different parts of the city.

• Perform solar thermal installations for energy monitoring to aid in understanding the solar thermal energy produced and consumed.

• Link diverse energy plants to the city's energy system for district heating, district cooling, and power grid.

• Build large scale bio–fueled combined heat and power (CHP) system for producing electricity and heat by renewables and organic household waste. The incineration of waste is used to produce energy for heating systems.

It is worth noting that some of the above installations depend on the geographical location and climate of the city as well as its energy needs. Today, solar panels often cost less than on-grid electricity. Moreover, if all buildings’ electricity is produced with solar energy, carbon emissions can be reduced by more than 50% compared to baseline in sustainable cities by 2030. Therefore, it is important to aim for shifting electric supply from 100% large-scale to 100% local solar power.

The main goal of the renewable energy sources and technologies strategy is to phase in renewables and phase out fossil fuels by 2050, resulting in 100% locally produced electricity and heat from clean sources in most districts and ultimately supporting the entire geographical area of data-driven smart eco-cities of the future. This kind of transformational change requires a strategic roadmap, i.e. a time-based plan that defines a future outcome and determines and assesses the decisive steps needed to reach it.

Smart Sustainable Waste Management

To achieve far more resource-efficient use of waste that has minimal impacts on the environment requires developing and implementing a number of measures and solutions as part of smart sustainable waste management. This strategy encompasses seven substrategies, namely:

1. Convenient and smart waste collecting system

2. Vacuum waste chutes

3. Food waste disposers

4. Biogas digesters

5. Wastewater and sewage treatment system

6. Biological waste separation procedures

Sustainable Waste Management

The key pathways needed for executing the sustainable waste management strategy are:

• Standardize the planning of sorting facilities for separating packaging, food waste, and mixed waste, and ensure that all properties have access to these facilities.

• Build and evenly distribute large waste sorting stations throughout the city, and connect them to the city’s waste infrastructure.

• Create and implement the relevant regulatory instruments with respect to waste management, and monitor progress to ensure the effective use in terms of the extent they yield desired results.

• Adhere to the waste hierarchy that reduces the quantity of the produced waste and the hazard it poses and prioritizes material-efficient products, thereby placing emphasis on recycling, reuse, and minimization of consumption in all its cycles.

• Use ICT to substitute for physical products.

• Design the waste sorting system in a way that is accessible and makes it easy for the residents to sort their waste in a safe and sustainable manner.

• Develop and disseminate easy-to-understand guidelines for sorting waste at the source.

• Ensure a high degree of waste separation across the city.

• Consider converting the food waste collected throughout the city into bio–fertilizer that can replace artificial fertilizer on agricultural fields.

• Build wastewater and sewage systems in the city, and integrate them in the city treatments plants

• Recognize that wastewater and sewage fractions are important energy resources (i.e. biogas fuels) and integrate them in the sustainable energy system.

• Develop and implement measures for influencing behaviors through engaging residents as part of environmental stewardship, as well as promoting sustainable habits and lifestyles.

• Set the following targets for sustainable waste management when planning new districts:

  • ○100% of the kitchen of the dwellings have waste disposal units.

  • ○100% of the properties have access to a vacuum waste chutes system in the residential courtyards that is able to transport non-organic waste underground.

  • ○Waste separation units are close to home for sorting paper and packaging materials, food waste, and mixed waste.

  • ○Wastewater and sewage treatment systems are installed and operate effectively in the city.

  • ○Closed eco–cycles function properly.

Smart Management of Waste Collection

Smart waste collection systems are becoming more and more wide-spread, and many cities across the globe are already implementing this solution in the city management programs. Typically, smart management of waste collection involves adopting data-driven resolutions to improve the efficiency of the city management, especially in relation to the urban areas lacking vacuum waste chutes systems. The key pathways for executing the strategy of smart management of waste collection are:

• Install smart waste collection system in the city:

  • ○Use sensors to allow to determine the degree of the fulness of waste containers, the level of the collected waste, independent of the nature of the recoverable waste.

  • ○Transmit the information received from these sensors via the mobile network to cloud storage for processing, analysis, and visualization.

  • ○Use the obtained results to allow the sanitation workers to plan the collection routes of their waste disposal trucks in the real-time mode based on the degree of fullness.

• Implement the smart waste collection system where needed.

• Develop and implement the BigBelly solution.

Smart Urban Metabolism

As a model used for describing and analyzing energy and materials flows in the city and their relationship with its infrastructure and activities, urban metabolism serves to maintain the functional and evolutionary states of the city as a socio-technical organism. Looking at data-driven smart eco-cities through a metabolic lens, a framework through which to successfully model the flows of their systems becomes of high importance and interest. This aids in understanding the relationship between human activities and the natural environment by studying the interactions of human systems and natural systems in the urban sphere. Indeed, urban metabolism provides a platform through which the implications of the different dimensions of sustainability can be considered. Below are the key pathways for executing the smart urban metabolism strategy:

• Develop and implement a smart urban metabolism framework based on real-time data, high temporal resolution, high spatial resolution, and continuous visualization of materials and energy flows to different city stakeholders and at different social scales.

• Use multiple key performance indicators (KPIs) that need to be based on real-time data generation from heterogenous sources and to be fed back on five spatial scales (household, building, neighborhood, district, and city) on the relevant interfaces developed for different audiences.

• Use dynamic and high resolution meter data for the evaluation of energy consumption in households and buildings. This is to increase the level of detail in the evaluation results and ease the detection of deviations in the performance of structures.

• Find more effective and innovative ways to deal with the challenges, barriers, and issues pertaining to the smart urban metabolism framework:

  • ○Access to and integration of siloed data from the different owners of data.

  • ○Privacy to motivate people to be actively involved in providing data.

  • ○The technical issues related to sensor technology, big data analytics, and emission factors.

  • ○Shortcomings concerning the use of dynamic and high resolution meter data for the evaluation of energy consumption, data collection and management, preservation of personal integrity, and incentives to react to the given evaluation information.

• Use diverse communication tools and methods for behavioral change, including:

  • ○Sustainable human computer interaction (HCI);

  • ○Eco-visualization;

  • ○Augmented reality;

  • ○Computers and smartphones;

  • ○Persuasive technology; and

• Climate pervasive services.

• Use data-intensive scientific methods for studying urban metabolism to provide harmonized indicators for environmental sustainability assessment and for quantifying GHG emissions of the city, as well as for urban planning and policy analysis.

Smart Environmental Monitoring

Air pollutants as atmospheric substances—especially anthropogenic—have negative impacts on the environment, as well as pose a high environmental risk to human health, so too is noise pollution, both direct and indirect. Noise pollution denotes harmful outdoor sound with road traffic being the major contributor. The demand for the smart systems that monitor the quality of the environment has increased due to the elevation of pollutants in the atmosphere. New and emerging technologies allow a real-time tracking capability of the different substances spread in the air, as well as applying preventive measures in a timely manner. Air pollution is due to several gases and dust, such as particulate matter (PM 2.5 and PM 10), Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Carbon Monoxide (CO), and Carbon Dioxide (CO2). Because air pollution and Greenhouse Gases (GHG) emissions are often released from the same sources, curbing GHG emissions in an effort to slow climate change also reduces air pollutants, such as PM 2.5. Reducing these co-emitted air pollutants improves air quality and benefits human health. GHG emissions are mostly associated with energy and transport sectors. Below are the key pathways for executing the environmental monitoring strategy:

• Develop and implement more effective mechanisms to get consumers and producers to use innovative solutions to reduce GHG emissions to levels that are economically, environmentally, and socially sustainable.

• Develop and implement environmental control systems associated with energy efficiency (e.g. smart meters, sensors, automation devices, monitors, etc.).

• Convert the small–scale tests performed in the areas of air pollution and noise pollution into pilot projects and then transition to a large-scale deployment and implementation.

• Install a sufficient number of automatic stations that collect information about air pollution in different city areas.

• Devise and implement solutions for control over air pollution that analyze the data collected from sensors on the level of air pollution in the different areas of the city to plan and introduce environmental measures.

• Develop and implement different prevention systems, including monitoring, forecasting, and modeling based on artificial neural networks for enhancing decision-making pertaining to the removal of the different types of pollutants detrimental to public health.

• Use air quality prediction data to prompt new businesses to provide better services to communities as well as the national map website to provide an incentive to government to release more data, in a searchable and reusable format, into communities.

• Facilitate the operation of the air quality monitors by regulatory agencies and researchers to investigate the quality of air and the effects of air pollution.

• Diagnose noise pollution with crowd-sensing and ubiquitous data to reveal the fine-grained noise situation and to analyze the composition of noises in different locations by using complaint data together with road network data, points of interests, and social media. The fine-grained information of noise can inform citizens' daily decision-making as well as official policymakers on tackling noise pollution.

• Devise and implement solutions for noise pollution control that analyze the data collected from sensors on the level of noise pollution for planning of work to reduce it. Such solutions should enable optimizing and centralizing the collection, integration, processing, and dissemination of information by the noise sensors of different suppliers and sound level meters distributed throughout the city.

• Use the data recorded by the various sensors reporting in real-time such parameters as air quality, noise levels, temperature, humidity, and gases dust particles concentrated in particular urban environments to analyze the impacts of the measures taken to improve the state of the environment, make inferences about the quality of the air, compile further programs for environment protection, and to identify the areas where further actions are to be undertaken.

• Create living labs for environmental monitoring management to provide a variety of services by using sensors to measure a range of physical parameters. The active sensors recording the relative and appropriate information for the services should be spread across the different zones of the city for obtaining the accurate data for these services. The collected data can be used to increase the knowledge of the most important city problems that need to be solved.

• Implement an integrated automated environmental protection system in the city. The results of measurements should be published online platforms to be visited by special software developers on a monthly basis.

• Promote easy-to-use and easy-to-set-up hardware and software for environmental monitoring systems (sensors and base units) among businesses, organizations, and institutions in the city to:

  • ○Measure and log a range of environmental conditions (e.g. relative humidity, temperature, differential pressure, pressure, flow, lux and carbon dioxide) in real-time;

  • ○Track and provide early warnings in case of critical events or unfavorable conditions before they turn into disasters; and

  • ○Provide various monitoring solutions with regard to server rooms, data centers, storage facilities, and labs to organizational and institutional units, as well as to those related to the ICT infrastructure of the city, such as horizontal information systems, analytical centers, and operations centers.

• Use hardware that provide the possibility to view the data via webpages using cloud computing and fog computing solutions.

• Use software programs that offer charts and graphics and various alarming functions, and allow to establish daily, weekly, monthly, or personalized reports with all of the statistical data required for sharing with other city departments.

• Commit to further developing environmental monitoring technologies and enhancing their applications in the future to guarantee a maximized effect of the use of the information collected about the state of the environment, This is due to the challenges of enacting environmental monitoring nowadays, notably the effective integration of multiple environmental data sources originating from different environmental networks and institutions. This integration requires specialized observation equipment, tools, techniques, and models to establish air pollutant concentrations at different spatial and temporal scales.

Important to note is that the smart environmental monitoring strategy is complementary to the smart grid strategy, which indeed aims to control GHG emissions. Smart environmental control systems can help to collect critical information to make better policy decisions to reduce GHG emissions. They can also guide citizens on making their own efforts to reduce GHG emissions.

Smart Street Lighting

The city-wide street lighting system provides tremendous opportunities for modern cities to collect huge amounts of data from urban environments and to transfer them to special centers for their subsequent processing and analysis for enhancing decision making associated with numerous uses and applications. This can be used to make urban living more environmentally sustainable and to enhance the quality of life for citizens. Street lighting is one of the most interesting pathway to using and exploiting the IoT and big data analytics in future cities. Thus, it can be expanded beyond what is originally used for. The key pathways needed for executing the strategy of smart street lighting:

• Develop and implement the smart street lighting system and integrate it into the city-wide lighting infrastructure to enable the use of numerous innovative solutions related to transport, traffic, mobility, air and noise pollution, parking, safety, public Wi-Fi, and so on.

• Leverage the city-wide lighting infrastructure in achieving ambitious environmental goals at a lower cost given the pervasiveness, high visual impact, and cost-effectiveness of the street lighting system, in addition to its connection to the smart power grid system.

• Replace the street lights across the city with LED-based lighting system together with an IoT-based sensor network for advanced programmable features related to energy and the environment.

• Use the smart street lighting system to reduce the operational costs and optimize the energy efficiency of public-lighting system, as well as to reduce the risk of traffic collisions.

• Use smart street lights for nighttime cycling based on context-aware technologies.

Smart Urban Infrastructure Management

Advanced ICT will be focused on defining critical problems and events that might emerge rapidly and unexpectedly across the city. Analyzing and identifying such problems and events is of great importance to urban sustainability and resilience. The smart management of the essential urban infrastructure involves monitoring and controlling its structural conditions in terms of potential changes that can increase risks and hazards as well as compromise safety and quality. In this context, data-driven smart technologies and solutions tend to be mostly justified by the high significance of the natural resources such infrastructure utilizes or involves in its operation. The key pathways for employing the strategy of the smart management of urban infrastructure:

• Support smarter transport, electricity, water, waste, and lighting networks in ways that can optimize resource efficiency and reliability and achieve more benefits with less expenditure and investment.

• Develop and implement new technologies for enhancing incident management, improving emergency response coordination, harnessing synergies between different components, minimizing risks, ensuring safety and service quality, and reducing operational costs.

• Develop and implement new technologies for coordinating activities between various operators and service providers of the essential urban infrastructures in regard to scheduling repair and maintenance in a more efficient and effective way.

• Relate sustainable and smart urban infrastructures to their operational functioning, operative management, and short-term planning through monitoring, automation, control, optimization, and improvements using advanced ICT, especially the IoT and big data analytics.

• Analyze and investigate longer term sustainable and smart urban infrastructure needs and demands up to 2050—and use new technologies to meet them in a timely manner.

• Use joined-up planning to develop and implement new urban intelligence and planning functions that generate the kind of structures, systems, and forms that improve and maintain the sustainability, efficiency, and resiliency of the city.

Economic Infrastructure

Generally, economic infrastructure refers to the facilities, activities, and services that support the operation and development of all the sectors of the economy. These facilities, activities and services help in increasing the overall productivity of the economy, as well as play an essential role in facilitating the running of economic sectors. Important to note is that the essential urban infrastructure embodies economic infrastructure, the internal facilities of the city that make business activity possible or promote economic activity, such as communication, transportation, distribution networks, and energy supply systems. Here, economic infrastructure focuses on the facilities, activities, and services associated with the practices and competences of civic institutions and urban centers whose mandate is improving economic and environmental sustainability. Accordingly, economic infrastructure encompasses the following seven strategies:

1. Green–tech innovation

2. Sustainable innovation

3. Sustainable business development

4. Green entrepreneurship

5. Quadruple helix as a model of synergic collaboration between the city stakeholders

6. R&D projects

7. Regional cooperation

Below are the key pathways for executing the aforementioned strategies:

• Promote regional collaboration to enhance sustainable business development.

• Make detailed regular plans for business development where the economic goals of sustainability are coupled with the targeted measures.

• Create arenas where politicians, business actors, and public servants meet to discuss questions and issues related to economic and environmental sustainability.

• Create frameworks for university-industry-government-public-environment interactions within a knowledge and circular economy.

• Support collaboration and networking with business actors to enhance knowledge and information sharing.

• Develop higher educational programs that integrate research into business development.

• Intensify collaboration between businesses, institutions, and research centers.

• Inspire and stimulate local green entrepreneurship by providing financial support and counseling and by offering awards to young entrepreneurs.

• Support sustainable innovation by incentivizing economic actors and business organizations.

• Create opportunities for aligning sustainability transition and economic goals in order to mobilize the business sector toward circularity.

• Establish research centers for entrepreneurship, innovation, and learning.

• Create R&D projects for eco-city development in the medium and long term based on partnerships between government, academia, and industry.

• Transform new successful sustainable urban development projects into sites that attract new investments, ventures, study visits, further development initiatives, and international interests.

• Ensure collaboration on and alignment with a shared vision of sustainability among companies, organizations, and institutions with different interests and goals.

• Establish research centers for environmental sustainability.

• Establish innovation centers for green energy technology.

• Transform innovation centers into international meeting places where the city, the business community, and the research community work collaboratively to profile and demonstrate know–how in green energy technology.

• Establish research and innovation centers for zero emission neighborhoods.

• Establish living labs for zero-emission/net-zero energy buildings as multipurpose experimental facilities to study various technologies in real-world settings.

• Support green energy technology innovation projects through funding schemes, advocating the adoption of environmentally friendly products and services and encouraging local environmental programs.

• Create arenas where industry experts, businesses, politicians, and citizens meet to discuss environmental problems and potential solutions.

• Establish competence centers for economic and environmental sustainability.

• Establish competence centers for sustainable business model innovation.

Social Infrastructure

Social infrastructure entails the development and maintenance of the basic facilities that are necessary for human development. It is concerned with the supply of such services as to meet the basic needs of a society. In other words, social infrastructure typically includes assets that accommodate social services. These are provided by a city government, either through the public sector (or related entities), or the financing of private provision of services. A huge part of new digital technologies, innovative solutions, interactive platforms, and diverse forms of public-private cooperation have become of critical importance to overcome the social challenges and to bring about the needed transformations in a number of social domains that eco-cities are facing. This is at the core of the assets of the social infrastructure of data-driven smart eco-cities of the future, particularly in relation to citizen participation, public safety, healthcare, and education and training (in addition to sanitation, drinking water, community support, housing, recreation, sewerage, etc.). Against the backdrop of this study, social infrastructure focuses on the following three strategies:

1. Smart citizen participation

2. Smart public safety

3. Smart healthcare

Smart Citizens: Participation and Consultation

Social infrastructure is about people. Therefore, the involvement of citizens in the management and planning of data-driven smart eco-cities of the future using information systems is crucial to making actual progress toward social sustainability. Such involvement is associated with the adoption of the key resolutions related to living, which intend to improve the level of satisfaction and increase the level of confidence and trust among citizens in the city administration. The strategy “participation and consultation” aims to stimulate citizens' interest in taking part in the planning and development of the city. Research, knowledge development, and experience feedback are important preconditions for solving complex challenges. The key pathways for executing the participation and consultation strategy are:

• Develop online platforms to engage citizens and make it easier for them to find out about different issues of planning and land use.

• Develop crowdsourcing platforms to address important city issues related to different areas.

• Establish a platform to enable citizens to influence their experience of the city by providing feedbacks and ratings.

• Create a platform where citizens can participate in the surveys organized by the city administration, which can use the related data to adopt the resolutions in relation to the different domains of city life.

• Create a platform to engage more citizens in dialogue so as to gather input on their needs and demands (e.g. buss timing, playgrounds, parking lots, parks, ICT system reliability, and mobile coverage indoors), to evaluate all their suggestions, and to identify and solve important issues. Citizens can suggest ideas that can be put to a vote among the registered users of digital platforms for polls.

• Create a platform to enable citizens to communicate as well as track the status and control the execution of their complaints related to city issues.

• Create special portals to enable citizens to report the economic problems existing in the city in response to the adverse effects of urbanization, pandemics, and disasters.

• Create diverse platforms to allow citizens to participate in urban technologies and policies, including:

  • ○Classrooms for learning about the uses and applications of and innovating in emerging digital technologies;

  • ○Entrepreneurial spaces for attracting startups and skilled innovators to create and promote new technologies

  • ○Co-innovation centers for enabling close collaboration among different city stakeholders;

  • ○Participatory platforms for connecting city stakeholders to support decision-making processes; and

  • ○Democracy platforms for enabling citizens to discuss government proposals as well as submit their own.

• Create city councils for remote service provision by public agencies and mobile kiosks.

• Develop and implement new technologies that offer the prospect of ending the digital divide, provided that they do not open up other kinds of divides.

• Develop data-driven projects to identify public trends that can be considered when developing programs and initiatives for urban development.

• Support and strengthen the technologies that ensure widespread citizen participation through enhanced security measures and privacy mechanisms.

Smart Public Safety

It is highly important to develop a much deeper and more informed understanding of the risks, threats, and hazards surrounding the city. This requires a new set of data-driven technologies and collective decision-making processes. Data-driven approaches to urbanism enables understanding the city as strongly interlinked and coupled systems that generates unexpected and surprising dynamics. Emerging technologies are increasingly changing the nature of such dynamics by predicting them on multiple scales in terms of the properties and processes that stimulate change within the city system, thereby outsmarting it. The key pathways for executing the smart public safety strategy are:

• Use cutting-edge tools through established platforms to create awareness of situations, provide realistic scenarios for hazards, and strengthen resilience by integrating artificial intelligence, expert knowledge, and human experience.

• Make use of data-intensive science in decision-making processes with respect to natural disaster preparedness, responsiveness, and recovery.

• Monitor urban environments to inform authorities as well as alert citizens of potential risks, hazards, and vulnerabilities.

• Use environmental monitoring systems to track air pollution (e.g, harmful substances) in real time to prevent or mitigate adverse effects on public health.

• Use advanced simulation models to predict disease outbreaks and act accordingly to save lives and resources through taking preventive measures.

• Use data-driven approaches to hazard identification and risk assessment to provide immediate responses to potential threats.

• Use data-driven sentient computing to improve security by denying access to suspicious users to public places.

• Use data analytics to investigate transportation–related safety and health issues and inform the responsible public and private entities to make improvements accordingly.

Smart Healthcare

One of the key areas targeted by technological advancements and innovations is human health. Medical systems and healthcare services are at the core of the IoT and big data applications. Healthcare management is one of the areas where the highest level of technology development and adoption is observed. The use of data analytics and personal wearable devices in medicine for the diagnosis and treatment of patients is one of the most promising areas of applied data-driven solutions in modern cities. Therefore, the focus should be on the electronization of medical services to enhance the quality of healthcare provided to all citizens and thus their well-being, as well as to upraise the effectiveness and efficiency of health system management. This entails using advanced tools, powerful computational processes, and innovative systems, such as embedded sensors and actuators, database system integration, management and monitoring software, simulation models, and decision support systems. The key pathways for executing the smart healthcare strategy are:

• Inform citizens about new healthcare policies and medical discoveries and rapidly disseminate information about disease outbreaks.

• Use advanced analytics techniques to analyze and interpret the huge datasets on health to improve the outcomes of healthcare with respect to those conditions that play out over longer times.

• Implement applied data-driven solutions in medicine for diagnosis and treatment by actively involving healthcare institutions, medical agencies, think tanks, and biotechnology companies as partners.

• Implement applied data-driven solutions to influence legislators on changes in regulating the medical and pharmaceutical industry.

• Encourage public and private medical organizations to adopt big data technology in their activities in terms of the implementation of eHealth platforms to accumulate, store, and deliver access to information about citizen health and medical history. The state-of-the-art technologies of big data analysis can be used to:

  • ○Perform accurate forecasts of the load on medical services and activity planning;

  • ○Evaluate the efficiency of educational programs, the quality of the obtained data, and the level of satisfaction of employers; and

  • ○Conduct health trend analysis of citizens.

• Connect medical centers, doctors, and patients with health data repositories and management software programs and sensing and communication capabilities to optimize the efficiency and performance of healthcare systems in terms of monitoring, traceability, and accessibility.

• Employ monitoring medical devices to remotely detect anomalies, gather patients’ behavioral information, detect changes in their normal parameters to help improve the quality of recommendations and the accuracy of diagnosis.

• Gather all information about human health and treatment in electronic health record (EMRs) to allow physicians from different medical institutions to access patients' medical records and to enable patients to participate fully in healthcare decisions.

• Gather and analyze information on health indicators from nonspecific devices, such as bracelets, smart watches, and sensors, as well as special medical devices.

• Establish a situation center to monitor the availability of and demand for medical services by analyzing the amount of appointments to doctors.

• Define inspection priorities and schedules based on the analysis of data on health standards in terms of checking the condition of hospitals and procedures and the execution of business rules.

• Inspect the recipients of health benefits based on the analysis of data to determine the level of compliance.

• Develop and implement the unified medical information and analytical system for healthcare. Such system comprises communication center, electronic registry, electronic health record, electronic prescription, disability certificates, laboratory services, and personalized record-keeping. It allows combining a variety of medical services and digitally collecting and analyzing data.

• Set the following targets prior to implementing the large-scale system of electronization:

  • ○Increase the transparency of medical facilities for citizens.

  • ○Raise the trust of citizens in health care system

  • ○Reduce queues in polyclinics by collecting and analyzing information on the flow of patients and the demand for medical services using a system of electronic records to set up appointments.

  • ○Distribute workers and doctors in healthcare centers based on data-driven decisions.

Discussion

The main outcome of this study is an empirically informed integrated model for strategic sustainable urban development. This study entails identifying a set of planning actions and policy measures that enable to build and achieve the status of data-driven smart eco-cities in terms of integrating their green infrastructure, sustainable urban infrastructure, smart urban infrastructure, economic infrastructure, and social infrastructure. Three case studies are involved in the empirical research conducted to inform the development of the integrated model. The first case study showed that the eco-city district model involves mainly design and technology as the core strategies and solutions for achieving urban sustainability, in addition to behavioral change. At the core of this model is the clear synergy between the underlying core strategies and solutions in terms of their cooperation to produce combined effects greater than the sum of their separate effects with respect to the benefits of sustainability. However, the environmental goals of sustainability remain at the core of planning, while the economic and social goals of sustainability still play second fiddle in eco-city development. Nevertheless, it was observed that new measures are being implemented to strengthen the influence of these goals over urban planning and development practices. Concerning the second case study, it showed that the data-driven smart city has a high level of the development of applied data-driven technologies and their implementation in the different administration spheres of the city in order to optimize and enhance performance as regards the different aspects of sustainability. In this respect, a number of technical and institutional competences are employed and established to improve the different areas of sustainability, notably horizontal information platforms, operations centers, dashboards, educational institutes and training programs, innovation labs, research centers, and strategic planning and policy offices. The outcome of this study demonstrates the untapped synergistic potential of the integration of innovative solutions and sustainable strategies on the basis of the IoT and big data technologies. Regarding the third case study, it corroborated that smart grids, smart meters, smart buildings, smart environmental monitoring, and smart urban metabolism are the main data-driven solutions applied for improving and advancing environmental sustainability in eco-cities and smart cities combined. There is a clear synergy between these solutions in terms of their cooperation to produce combined effects greater than the sum of their separate effects—with regard to the environment.

In light of the above, the data-driven smart city model shares the challenges of sustainable development with the eco-city district model, with the main difference being that it focuses on the use and adoption of data-driven technologies and solutions and related technical and institutional competences to overcome these challenges—rather than on the planning practices and design strategies of ecological sustainability. Concerning the environmentally data-driven smart sustainable city model, it emphasizes the dimension of environmental sustainability and employs data-driven technology solutions to reach environmental targets. In this sense, this model combines concepts and ideas from both the eco-city and the data-driven smart city. These two models are increasingly being merged together in a bid to overcome the significant challenges posed by climate change in the face of the escalating trend of urbanization. While both of these approaches to urban development implement data-driven technology solutions to improve and advance environmental sustainability, they remain significantly divergent with respect to their priorities, visions, policies, strategies, pathways, and goals, thereby the meaningfulness of their integration in the third case study.

Regardless, it has become increasingly feasible to attain important improvements of sustainability by integrating eco-urbanism and smart urbanism thanks to the proven role and untapped potential of data-driven technologies for maximizing the benefits of sustainability. As a result, there has been a conscious push for eco-cities across the globe to be smarter and thus more sustainable by developing and implementing data-driven technology solutions so as to optimize operational efficiency, enhance functions, strengthen infrastructure resilience, and improve social equity and life quality. This trend is evinced by many topical studies conducted recently on eco-cities (e.g. Caprotti, 2020; Caprotti et al., 2017; De Jong et al., 2015; Pasichnyi et al., 2019; Shahrokni et al., 2014; Shahrokni et al., 2014; Shahrokni et al., 2015; Späth, 2017; Tan et al., 2017; Thornbush & Golubchikov, 2019). This is owing to the core enabling and driving technologies of the IoT and big data analytics offered by smart cities in relation to sustainability (e.g. Angelidou et al., 2018; Bibri, 2019b, 2020d, 2021a, 2021b, 2021c, 2021d, 2021e; Bibri & Krogstie, 2020b; Nikitin et al., 2016; Noori et al., 2020; Perera et al., 2017; Silva et al., 2018; Stübinger & Schneider, 2020; Trencher, 2019; Zawieska & Pieriegud, 2018; Zhuravleva et al., 2019). In particular, the key role of smart cities lies in connecting the aforementioned infrastructures of existing eco-cities. This connection, as enabled by advanced ICT as essentially network-based, is a way to leverage the collective intelligence of emerging data-driven smart eco-cities through the synergic nature of ICT in regard to producing the benefits of sustainability. This can be accomplished by harnessing the vast troves of data that can be generated from across many urban domains thanks to advanced computational analytics techniques as well as urban operation systems and operations and analytical centers (e.g. Batty et al., 2012; Bibri, 2019c; Kitchin, 2014, 2016; Kitchin et al., 2015; Nikitin et al., 2016).

The primary role of big data lies in enabling information flows and channels, coordination mechanisms, powerful analytics, evidence-based decisions, and learning and sharing processes involving divergent constituents and heterogenous collective and individual actors as data agents. These are indeed the most significant challenges that are currently facing eco-cities, coupled with the dispersion of power. These complex conditions are continuously exacerbated by the unpredictability of environmental, socio-economic, and demographic changes. On the face of it, the road ahead promises to be exciting as more cities become aware of the clear prospect of integrating eco-urbanism and smart urbanism—for meaningful uses and collective advantages. However, it is too early to predict the full scale of the potential negative consequences and hidden pitfalls associated with smart urbanism (e.g. Kitchin, 2014, 2016, 2020; Marvin et al., 2015; Martin et al., 2018; Söderström et al., 2014; Verrest & Pfeffer, 2019), including technocratic reductionism, technocentricity, city governance corporatization, dataveillance and geo-surveillance, privacy encroachment, and mind control and manipulation.

Furthermore, eco-cities are characterized by great specificities on multiple levels. This in turn shapes the way in which the IoT and big data technologies can be embedded in the fabrics of eco-cities and be applied in urban operational management processes and development planning practices. Tu put it differently, eco-cities essentially exhibit key differences in how they prioritize and implement their strategies and solutions depending on many intertwined factors, including the kind of challenges they face and their significance. Khan, Hildingsson and Garting (2020) show that ecological sustainability remains local in that it is situated in the specific spatial, temporal, and political context of the eco-city projects under development. In other words, eco-city projects are associated with particular places, initiatives, histories, technologies, values, and perspectives. Particularly, as revealed by Joss and Cowley (2017) based on a comparative case study analysis, national policy is found to exercise a strong shaping role in what the notion of sustainable development for future cities is understood to be, which helps explain the considerable differences in priorities and approaches across countries. Furthermore, the IoT and big data technologies might work in one eco-city in a way that is different from another. Hence, they need sometimes be reworked to be applicable in the context where they are to be embedded. Especially, eco-cities do not have a unified agenda as a form of strategic planning, and data-driven decisions and solutions are unique to each eco-city, so are environmental, economic, and social challenges. Big data are the answer, but each eco-city sets its own questions based on what characterize it in regard to policies, strategies, pathways, goals, and priorities (Bibri & Krogstie, 2020c). Regardless, it is important for eco-cities to make the best use of their local opportunities and capabilities as well as to assess their potentials and constraints from a more integrated perspective. All in all, universal urban models are problematic and cannot be applicable in the same manner all over the world (e.g. Bibri, 2021b; Karvonen et al., 2019).

Conclusion

Conventional paradigms of eco-urbanism require new responses under the current circumstances of the escalating challenges of sustainability in light of the rise of digitalization and datafication. It is important to find and apply more effective ways of monitoring understanding, analyzing, planning, and managing emerging eco-cities in more innovative ways to achieve the desired outcomes of sustainability.

This paper aimed to develop an integrated model for strategic sustainable urban development based on empirical research in the form of three case studies. In so doing, it identified a series of actions and measures that need to be undertaken to transform the green infrastructure, sustainable urban infrastructure, smart urban infrastructure, economic infrastructure, and social infrastructure of data-driven smart eco-cities of the future. This empirically informed model for strategic sustainable urban development is meant to be clearly specific in terms of the underlying components based on the leading paradigms of urbanism (Figure 1).

Figure 1. An integrated model for strategic sustainable urban development.

This integrated model illustrates the combination and integration of the underlying components of data-driven smart eco-cities of the future in terms of their design strategies and technology solutions. It comprises three basic components: (1) eco-city design strategies and environmental technology solutions; (2) data-driven smart city technology solutions for sustainability, and (3) environmentally data-driven smart sustainable city solutions and strategies for environmental sustainability.

The value of this study lies in providing innovative ways of building future models for sustainable urban development as well as practical insights into developing strategic planning processes of transformative change toward sustainability based on integrated approaches. The proposed model serves to facilitate progress toward achieving the long-term goals of sustainability for those cities that are badging or regenerating themselves as ecological, or manifestly planning to be or become smart ecological in the era of big data.

Author contributions

The author read and approved the published version of this manuscript.

Acknowledgment

The author received no financial support for the research, authorship, and/or publication of this article

Disclosure statement

No potential conflict of interest was reported by the author(s).